>> Live from Las Vegas, it's the CUBE, Covering VMWorld 2018. Brought to you by VM Ware and it's ecosystem partners. >> Hey, welcome back to Las Vegas Mandalay Bay. Lisa Martin with Dave Vellante at VMWorld 2018 Day One. Dave, this has been an awesome day. >> Yeah, jam-packed and almost 1/3 of the way through, 94 guests, I think our biggest show ever. >> I think I'm going to say, I'm going to make up a word and say it's going to get awesomer because we have one of our distinguished alumni, Vaughn Stewart, >> Wow. VP of Technology Alliances and Strategy at Pure Storage, Vaughn, great to have you here. >> Lisa, Dave, thanks for having us back. >> Great to see you again. >> Yes, ditto. >> We had a blast hosting the CUBE at Pure//Accelerate just a couple months ago. >> We got T-shirts. >> But we were sporting our, yeah, in the context of the Bill Graham Civic. I feel too dressed-up actually for talking to Pure Storage. So some great momentum you guys had when we were there a few months ago, great momentum continues, quarterly revenue earnings just announced, 37% year-over-year growth, almost 400 new customers. Gartner, fifth year in a row, you guys are a leader in the Magic Quadrant for Solid-State Arrays, wow! >> Yeah a lot was shared last week with the financial results, right? Couple more just points of color-commentary, if you will. 309 million dollars, 27% of quarter-over-quarter, 35% of penetration of the Fortune 500, roughly 30% of the revenue comes from the cloud providers, say like clouds number eight through 500, on the Magic Quadrant, right, five years in a row being in that upper-right quarter, quadrant. And if you look back on it historically, just the players that have come and gone and their positions have changed and we've kind of been the foundational element in that corner, I think speaks to, how well we know the length of market, on top of all that, right, Pure Storage's first acquisition, right, StorReduce. >> Congratulations. >> For those of you who maybe haven't heard of StorReduce, start-up, their focus is on providing data deduplication across object stores, born in the cloud, Pure software play, I think we're going to continue to leverage that within it's current focus in market area as well as expand our, it's part of our cloud strategy and even maybe bring some of it into the current on-prem product portfolio. Lot's of opportunities available to us with that IP. >> So, you know, when you look back at the sort of, well first of all, flash, Solid-State, upper right. But there's life beyond flash arrays, right. So if you look at some of the early guys, you remember Astec, if that's even how you say it, Fusion, and a lot of people predicted, oh you know, same thing, everybody's going to catch up to Pure, but you guys kept innovating, cloud is now a fly wheel for you guys, you really went hard after it. So I wonder if you could talk about the evolution and sort of phases as you guys see them of the company? >> Yeah so for your audience, I think one way to look at this with a start-up is when your founders have an idea of bringing a product to market, you have to be very laser-focused which means there's trade-offs, right, there's a lot of things that you can't do so that you can bring your technology to bear, your product, you've got to you know be able to gain market share, right. Customers' revenue is kind of like the lifeblood early on. And we've evolved past that, right, there's been the passing on the torch last year with our change in CEO from Scott who moved on to be chairman of the board, bringing in Charlie, and I think we're really at this phase of the beginning of what I call Act II, along the way, flash array which is our flagship and our initial product, has helped customers adopt technologies through different business models, right, the Evergreen Storage play, us introducing non-volatile memory express into all of our products, you know, half of our customer shipments in Q2 were all NVMe, right, so. Allowing customers to adopt technologies in new models that they didn't have before that aren't rip and replacements has been a key to our success beyond the tech. Flash blades often up and running in net new areas of business opportunities for us like AI and ML. And now you get StorReduce, right, this cloud component. I would say that the legacy of Pure, that Act I that Scott built is going to continue to run for the next couple years kind of on auto-pilot. And that's not to be dismissive of the field that's got to go out and execute every, you know, every day, every quarter, but Charlie's vision about what we're going to evolve into, I mean we're really if, to use a baseball analogy because someone was talking Sox before the cameras went on >> Who could that have been? >> Yeah, yeah. (laughs) You know, we're in the beginning of the first inning, you know, StorReduce is just, I think the tip of what we're going to do. We got 1.1 billion in the bank, you know, we've got a little bit of capital to continue to invest in the portfolio. So right now the focus is on still, I think there's two ways to look at this. What I find most enterprise customers want to talk about is how do I merge three modern technologies, right? All-flash, hyper-conversion, and cloud? Give me a strategy that unifies them, not one that divides. And we can have a whole conversation on that. Then there's this whole other segment around analytics and AI which, you heard it here in the keynote this morning with Pat. Focus area, you know for VM Ware, AI is the modern version of what analytics were six years ago. And so this is something that I don't think all the practitioners here are aware of. It comes from a data science or the application side into the infrastructure, and we're trying to help people make a turnkey AI-ready infrastructure through the RE product within video so there's just a lot to talk about. >> And you can see those worlds coming together with, take cloud, take AI, take data, which is what you're all about. >> Yup. >> That's kind of the innovation sandwich of the next 10 years. It ain't Moore's Law anymore, right? It's AI, applying machine intelligence to the data and scaling a cloud. >> You know one of the things that Silicone Angle I think may have been at least the largest analyst firm that I saw jump on this early, was around the notion of bringing your data to the infrastructure. >> Yeah, absolutely. >> And then you guys pushed in, you guys leaned in really hard about three or four years ago on that the world is a hybrid model. It's not one or the other, it's all hybrid. And you even talked about the differences in the type of data sets and it's computational requirements and where it may or may not be placed, as well as you really leaned in on the interop requirements to cross the different silos. >> Yeah, that's right. >> So kudos to your research. >> Yeah, thank you, and we've quantified that. It's actually that whole idea of bringing the compute to the data, for example, wherever it resides. I mean that's a big, big business. If you look at the size of the market of those folks trying to replicate substantially cloud on-prem, it's 30 billion dollar businessing growing very, very rapidly. And you guys play in both sides of that, I mean that's what's impressive, you're not just on-prem, you're not just in cloud, you're hybrid. >> Here's a good example of how cloud evolves. We're really proud of our net promoter score, right. It's 86.6, top 1% of B2B businesses, right. I look at external points of validation whether it's a net promoter score, what an analyst firm ranks you at in their Magic Quadrant or others, as are you delivering to your customers your promise to them, right, you're marketing material. Part of why our score is so high is the product's reliability is there and it delivers. Underpinning that is we've got a predictive analytics technology that helps the arrays achieve greater than Six Nines availability, right? That component, that's Pure One, that was born in the cloud. That was born in AWS, and we talked about this in a session at our Accelerate conference, which is we've got greater than nine petabytes up there. Every time we do a new, we're working a new algorithm for AI to make our product better for our customers, we have to download a year's worth of historical data. That takes 45 days to download in stage. So we're moving it to a hybrid model. And what's it going to allow us to do? It's instantly going to help us reduce our cost and accelerate our AI initiatives by six X. And it's just a bridging of the technologies. Regardless of what you have, you have an all-flash array, you're a cloud provider, you're a hyper-converged. Sometimes your product teams look at the world with like, I got to hammer and that's a nail and what really provides sophisticated outcomes is when you can bridge the technologies based on results. >> Speaking of marketing messaging, some people, some companies like to say they are data-driven, or they will enable their customers to become data-driven. At Accelerate a few months ago, Pure Storage talked about data-centric architecture. Now we all hear data is the lifeblood, data is power, data is currency, it's none of those things unless an organization can harness it and extract the insights and act on them immediately. >> Right. >> Talk to us about the data-centric architecture. What is that, how have you seen that, we'll say, accelerate in momentum in the last few months? >> Great questions, so thank you for bringing that up. I think on the surface, one may look at a data-centric architecture message as being oh, that's what you would expect from a storage vendor to say, right? Sounds like something aligns to your products. And I think there was some inside baseball being shared, if you will, in that message, right? There was some telegraphing going on. Because at the core of the message, what we're trying to say is, your traditional applications tend to be more stove piped and siloed, right? What you see, and I'll take this through two levels, what you see with taking traditional applications or legacy apps and you virtualize them, and now you want this mobility where you can move the application around anywhere, all-flash or on-prem or into the cloud, that's one form of movement. Modern applications are distributed, right? There are a collection of processes, different data sets and the application's much more like a pipeline. And so when you look at data from a view of pipeline, you have to stop thinking about your silo that's wrapped around your one tool that you as a developer may have a responsibility for in the product or the code. >> Your God box, as it were, right. >> You got to figure out how does it work in a pipeline with others, how are you going to ingest data and hand off data? So in a data-centric architecture, we're trying to advocate that there's a value in shared architectures and in addition to this, there's been this whole market that's grown up over the last decade initially around analytics where their architectures were designed around DAS architectures. And you have to look back a little bit to get a understanding of where we are today which was, you go back ten or twelve years ago, it was really easy with the par of intel to bury a disc-based storage rate, no matter what size it was and which vendor put it out. You could saturate the IL bandwidth. Now we're at a day and age today, shared accelerated storage, fast network interconnect with non-viable memory express over fabric whether we're talking ethernet or fiber channel. I now have the latency that's within ten microseconds of direct attach storage. I get all the benefits of shared. And I get some new architectural models that may help me with costs and efficiencies. And so you're starting to see vendors in the software space follow in suit and so, for example, you've got Vertica releasing support for S3 on-prem. You've got VM Ware adding more fuel around VVOLS and interoperability between VVOLS, vSAN, and VM Cloud. There's more partners that have more activity going on that I can't share because they've got announcements coming through the second half of the year but vCloud Air just published in July a new paper on HDFS on remote storage regardless of the protocol so you're seeing all these DAS-centric vendors start to say, alright, our customer-base is telling us they need a shared model. So shared accelerated, flash, NVMe, NVMe over fabric, it's going to fuel new architectures that are more flexible. >> So I want to follow up with that because you're right, the data pipeline is elongating and it's getting quite complex. I mean if you're an AWS customer, which we are actually, if you use kinesics, DynamoDB, EC2, S3, you know Red Shift, etc. Those are all sort of different proprietary APIs. Sometimes you don't know what you should do where until after you get the bill. >> Right. >> Can you help solve that problem for customers and simplify that or are you just a piece of that chain? >> So we have a component within the chain but we're working with our field and our field technologists to help advise customers particularly around what I'd call like a cloud-first strategy. So, if we look outside of storage and you're looking in the cloud developers and it's function as a service, for example. >> Right. >> So we use our own case study, right, Pure One. We got hooked into function as a service within our provider. And what we've found was our ability to use multiple clouds, our ability to go hybrid-cloud, and our ability to actually take our analytics and be able to package it up and deliver it to dark side customers that, there's about a third of our customers that won't allows for their units to phone home, okay? Three-letter acronyms that run in the federal space. Cloud-first meant that we just take that function as a service and instead of making the direct API call put it in a container. Now once you're containerized, I can run it on any cloud. Right, and now again, cross-public cloud, hybrid, into private, and it gives you a lot of flexibility. So we're working on architectures and educational conversations, not just about the data pipeline and how your data has to transform as it goes through these different phases, but also at the higher level, really going to be leaning in on containerization and so the customers can have greater mobility, and again, we'll use our own use-case and evolution of Pure One is the front and center message there. >> I'd love to get your perspective, kind of changing the topic, on the ecosystem evolution. You've observed the VM Ware ecosystem. You remember well, I mean it's just strange that EMC ended up with this asset, right? I mean it's kind of unnatural and all of a sudden, boom, it explodes, and you had this storage company somewhat controlling, you had the storage cartel kind of which, VM Ware wanted to placate, so that was good, that sort of was a bulwark against EMC having too much control. Now you see Del's ownership, you see the AWS relationship. As an ecosystem partner who's now reached escape velocity and beyond, what do you make of all this? >> I think you have to look across Pat's time and before Pat to Diane, right? Diane made it clear, right, when there was acquisitions in play for VM Ware, right, she said, we'll never be owned by a server vendor. And so storage vendor acquires EMC, and for all the blustering of EMC control, there was never anything that was proprietary towards EMC with VM Ware, right. >> Right. >> The focus was on the entire partner ecosystem. That's a good bat, right, let the harbor vendors go battle out for who's got best in class, just deliver the VM software to the market. Allow VM Ware to go innovate on different timeframe than the storage layer. Now that Del is in the ownership seat, you have the same answers from Pat, when he sits down with Charlie it's like, look, we're going to be independent, we're going to be agnostic, we're going to take you as a partner to help us build frameworks. So for example, we're one of the lead design partners on NVMe over fabric, we're doing technology previews with vSphere in the booth. We're the fastest growing VVOL partner. So I know I'm making plugs here but I don't think anything's changed, right. I think VM Ware's business model's been brilliant to not become tied to any hardware partner and focus on what you do better than anyone else which has been delivering virtualization and what I really like about this show, and tell me if you think so, right. AWS was shared last year, right? Containers have been shared at this show for about four years. This year was a focus, right, it was AWS, it was containers, it was automate everything, and then inherently it brings security in as an inherent component of the products, right? These are really bold, strong investments that they've made that are new, right. So you see the evolution of VM Ware, and we're partnering with them on a number of these initiatives and there's nothing to share now. That'll be next year. >> Well and you're right, Vaughn, the picture's getting clearer. I thought Pat's keynote was very good this year, and crisper and more cogent relative to the strategy than last year and previous years. It's really starting to come together. Now what about the AWS piece because that's also a company with whom you have a relationship. So does the VM Ware, AWS partnership, is that a tailwind for you guys? Or is it, hey, we're trying to get the attention of AWS, too. >> So I would say our, so we signed a formal VM Ware alliance relationship this year, and I would say it's progressing well. What we can share with the market right now is minuscule to what we'll be sharing, say later in the year, beginning of next year. But for right now where we're at is, so we're a direct-connect partner, gold-level sponsor for their conference, re:Invent. With VM Ware and AWS and Pure as a three-way alliance and partnership, VM Cloud, VM C, is going to add support for iSCSI, that's a second-half of the year initiative, or fourth-quarter initiative, and we'll be there as a lead development partner supporting that framework when it comes online. It's going to open a lot more flexibility for us and our joint customers about adopting either your own on-prem hardware or running it on the Amazon hardware. Make it fit your business model whichever way you want to roll but make it fully interoperable and move the data and the compute instances seamlessly and non-disruptively. >> Guys. >> It helps to be a hot company. >> I wish we had more time. I'm hearing accelerated momentum and maybe some teasers that Vaughn dropped, >> Yes. That maybe the CUBE needs to be, yeah. >> We'll stay in touch. >> We'll get some more interviews. >> Yeah. >> (Laughs) Vaughn, thanks so much for joining Dave and me and sharing all this exciting news that's going on, and like I said, accelerated momentum, pun intended by the way. >> Thank you, thanks guys. >> Great to see you. >> We want to thank you for watching the CUBE for Dave Vellonte, I'm Lisa Martin with the CUBE at VM World Day One from Las Vegas, stick around, we'll be right back. (funky music) >> Hi, I'm John Walls. I've been with the CUBE for a couple years.

(lively music) >> Narrator: Live from Las Vegas, it's the CUBE covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. >> Okay, welcome back everyone. We are here live in Las Vegas, the Mandalay Bay for Oracle's Modern CX conference, hashtag Modern CX. This is the CUBE. I'm John Furrier Silicone Angle. My cost, Peter Burch with us for two days. Our next guest is Ron Corbisier. Owner and CEO of Relationship One. Back again, from last year. It was one of my memorable interviews last year. Welcome back-- >> Ron: Thank you for having me. >> to the cube. We went down and dirty last year. I remember we were having a great conversation about ad tech. If you've taken that video, it's on YouTube and look at it, I guarantee you, it's going to play right into what happened this year. Again, we predicted it. We didn't say AI but we did say we're going to see data really driving. That's what Oracle ended up locking in on daily. >> Yeah, absolutely. Data is going to be the underlying conversation for the next few years. We spoke, a lot, last year about martech stack. Actually, martech and ad tech colliding, coming together. All of that is being fueled by the mass quantities of data that we have as sales and marketing folks out there, to leverage and how do you use it. It's never about, do I have enough data? A lot of times you feel you, almost, have too much. But it's, now how can you use it appropriately? >> We were talking, before we came on camera here about that dynamic of ad tech and marteh collision which we talked about last year. It's interesting. If you just say digital, end-to-end, as a fabric, then you can still talk about these pillars of solutions but they're not silos. If you look at the holistic data approach and say, hey, if we're going to have horizontally scalable data which we want, frictionless less than 150 milliseconds responses they want to promote. You can still do your pillars but be open to data sharing versus here's my silent stack. I do this, I do this, that's shifted and that's what Oracle's main news is here. >> Yeah, absolutely. I think what you're seeing, even in, not only Oracle, that organizational level, people are taking a more holistic view of data that they own and data that they can enrich with external information, right? How does that information, then, fuel all of these other areas within customer experience within the CX world? How do you use that to provide better service? How do you use that information to optimize your sales efforts and from a marketing standpoint, obviously, my background, it's how do we leverage that to optimize our spend, optimize our communication, our orchestration, all of those pieces. It all comes down to that common language of data that we have access to. >> Tell me about the real time aspect cause we teased on it last time and we did talk about how to leverage some of the advertising opportunities and the role of data in real time. That's been a message here from batch to real time. The consumer's in motion all the time depending upon their context. How does real time fit into this? >> Yeah, this is the evolution of what we're seeing in the technology, right? Historically, you've built a campaign. You've, maybe, created some type of journey or persona. You're building content around very specific elements within a life cycle structure. Life cycles are not linear any longer. They never really were but they're, definitely, not now and you have to adapt very quickly. Leverage technology, to say, one of my saying, communicating and what channel but in more in a real time thing. You have to look at what was the last thing that individual did, the activity, all of that. Historically, you haven't had that depth or degree of real time lists. It's been more of a structured candance. That doesn't exist, right? That's not going to exist going forward. That's where things like AI which I always hesitate to use that term because it's the buzz word now of today. But tools that are more of that augmentation of how we do things. Leveraging the power of technology. That's going to change how we orchestrate things and how we communicate. >> I'm just looking at your tweet here. I want to bring this up because you mentioned AI and we were talking about it. Thanks to all who stopped by my MME 17 Modern Marketing Experience 17. A little bit of a jab at the messaging that's cool like that. Session on artificial intelligence. Loved all the support from my fellow modern marketers. What do you mean by that? You make a bold statement. Did you have courage? Did you stand tall? Did you call out AI? What was the conversation there? >> Well I called out the silliness of the term AI. I picked on that the marketers but I picked on the term We, as marketers, I call them the squirell moments that, as marketers, we're on to the next thing. I reviewed the past eight some years of these conferences and what were the topics, right? There were some topics that were transformational topics like how does marketing automation or organizational change or those type of things. Those are things that stick with you. There is things that are more timely things. Like predictive scoring and their tactics. There more things that I use as a marketer or sales person. What I was picking on with AI is that it's the buzz word. It gets you funding. It gets you people in a room for a conference, that's great. But it doesn't do anything by itself. It's really an enabler. It's a pervasive thing that combines machine cycle and data but you have to teach it, you have to incorporate it into your applications. As marketers, ultimately, it's going to change our tool set to make it better. It's more poking fun at the term-- >> We always say AI. I've said it on the CUBE, AI's BS. Although, I'm a software guy. I love AI because it really promotes software that has been very nuance. So, IOT, machine learning, this is very geeky computer science stuff that's super cool. Anything that can take that mainstream in the software world, I'm a big fan of. That being said, I think the augmentation is the real message which is, you can use machine learning, you can use software, use some technical things, to make things better. You said it on our earlier segment this morning which is there's a variety of things that you can automate away. >> The thing that's, and you mentioned earlier, it's the ability that we now have the ability to collect an enormous amount of data, that's relevant and important. And we now have the technology to, actually, do something with that data. But we still have to apply it and there's a lot of change that has to happen. The way AI is different from other systems is that, historically, financial systems, software would deliver and answer. It was highly stylized. It was rarely, a clear correspondence with the real world. We closed the books. How much money did we make? There was an answer and it came from some data structures that were defined within the system. Now we're trying to bring in the real world and have these technologies focus on the real world. And they're giving ranges of possible options. That is new. It's good and it's useful but it does not take the requirement for discretion out of the system. That's why it's the augmentation. >> Ron and I were talking last year about this, Peter and I. I think you're getting a trajectory that, I've been saying for a while and this is developing in real time here on the CUBE and also some of our commentary is the role of software development and DevOps that we've seen in Cloud, is moving into the front lines of business. Meaning their techniques. You're seeing Agile, already, being talked about. You're seeing standing up campaigns. Language, you can go to the Cloud stack and say, building blocks, EC2, S3, Cooper Netties, containers, micro services and apply that to marketing because there's a lot of parallels going on to the characteristics of the infrastructure. Certainly critical infrastructure to enabling infrastructure. It's interesting that you're seeing marketers being more savvy and inadative. What's your thoughts on that, a reaction? >> Yeah, it's the evolution though. If you go back to, we as marketers have been using rules engines, we've been using tools like collaborative filtering. You go back to late 90's, early 2000's when we were building recommendation engines in simple. That's algorithmic stuff, right? No different than we're doing today with pricing rules and all that stuff. The difference it that you now have more power to do it. You have the ability to do it more real time and on the fly. You use far more data. More computing power and more data. Not only your data that you own but data that you leverage from third party to really understand people. You have a wider lens. Historically, you're making recommendations based on what you had in a cart or some other things that people have bought that also had that in the cart, that's different now, right? With this type of technology, this enabling kind of world, you an look at a lot more data points to give you that. The problem is that anything around AI requires a couple of things. It is a dumb system so AI. (laughs) >> Still a computer. >> It's still a computer. Everyone forgets that for it to work, it has to learn. I have some friends who have built marketing tools on top of Watson, for example. It takes hundreds and hundreds of hours for it to start doing something. You have to train it. You have to, not only, give it the data, you have to train it. >> Even the word learning and training is misleading in may respects. At the end of the day it's software but what is new is it's being applied in richer, more complex domains. The recommendation engine used to be just for recommendation. Now we're using those same models and we're combining them and applying them to richer more complex domains. Yet, ideally, the software's not getting more difficult to use. And I think what really makes this compelling, as a software engineer, is that we're doing all this more complexity but we're packing it and making it simpler. >> I think that's the point of where Oracle's going and why they don't call it AI. They're using it more the adaptive. Because they're thinking of it at the micro service level. They're thinking of how can they make these widgets of functionality to better the tools we have. To incorporate it into not make it so a jump forward in our tool set. It's just now, an augmented component of what we do today. >> It's, almost, a stack approach. You got foundational building blocks and at the top is high velocity, highly dynamic apps and you could argue, we were talking that the CMO's going to be an app shop, some day. This banks the question and I'd like to get both of you guys to weigh in on this. Because this is a question that I'd like to get on the record. What is modern marketing these days? Define modern marketing because what we're getting at here is, to your point of the evolution is we've seen this movie before. Is it a replatforming? Is it a building block approach? What is a modern marketer? What is a modern marketer mean? How do you execute that? >> I think it's quick and nimble and adaptive. The whole point of modern marketing is that you're always looking at how you can rethink, how you can optimize, how you can leverage technology to do things. It's not about replacing head count with a machine or a tool or a tech. It's really about how do you leverage that head count more effectively? How can you focus on optimization using those technologies. Modern marketing is, again, probably another buzz word but just like modern sales, modern commerce, all of that. It's really about how do you enable it with that stack do better. >> So, is it fashion or is it like hey, there's a modern marketer over there, look at what he or she is wearing. Or is it more technology based that's got some fundamental foundational shifts that are being worked on or both? >> It's leveraging technology and it's leveraging data more effectively and creatively. It's not being stuck with a prescriptive approach on campaign and orchestration and building. It still requires strategy and all of that but it's really how you approach it. >> So, how you think of it. What's your angle on this? >> That's a great question. And that's why I giggled about it. I think you gave a great answer. The three key precepts of Agile are, iterative, opportunistic and empirical and it's nimble quick and you change. But to me, I'll answer the question this way. Modern marketing focuses on delivering value to the customer not back into the business. It used to be that you would deliver into the business. He'd say, oh, we give you a whole bunch of new leads. We give you a whole bunch of this. If along the way, it created value for the customer, that's okay. But more often that not, it was annoying. As customer's can share their experience and share information about how (mumbles) engaged them, that's amplified. Annoying gets amplified. I think if you focus on are you creating value for the customer, you also end up with the derivative element that you're accelerating leads, they are in the process and where they are in the journey. The way I'd answer it. It's not distinct from yours but the idea of modern marketing focuses on creating value for the customer. The only way you, consisting do that is by being nimble and blah-blah-blah-blah-blah. >> I agree, in the same thing though. A core tenant, if you will, of modern marketing is absolutely. It is the value proposition. It's also making sure you understand the impact of the value of proposition The velocity of the pipeline, the impact on revenue, all of those things right? Because it's all about that value which it has to be, from a customers perspective but you're not doing all of the other pieces. You're not going to justify the spend. You're not going to get all of those together. >> Let me see if I can thread the two points together. Cause what I'm seeing, by listening is, you mentioned, the main thing in my mind was the data. That's different right? You're saying okay, thing differently, talk to the customer and the value to the enterprise value is being created through a different mechanism versus just serving it. >> Not really, not really. The fundamental focus, historically, of marketing has been what are we doing for the business? What are we doing for sales? Now, if we focus on, now you say well no. We have to created value for the customer in every thing we do, then we get permission to do things differently. We get more data out of the customer because the trust is there. We're allowed to bias the customer to the next, best option. >> I'm trying to answer my questions. I can see your point. My point is this, the modern marketer is defined by doing it. The business practices it a little bit differently to achieve the same thing. >> By focusing or creating value they have to do things differently and now they can because technology allows them to do it. >> We saw Time Warner, they weren't using data prior. That's a little different. If you go outward to go in, it's a great value while doing the table stake stuff. >> It's changing strategically thinking different of how you do it. Creating that value proposition's very different and also being able to measure and optimize are you doing it correctly? Is it having impact on the business? Most of my customers are not for profits They, actually, have to show, bottom line an impact. All of that requires data and speed and velocity in which we have to run requires tech. >> They got gestures in the market with customers. They have that touch point. They can leverage that. >> Here's (mumbles) modern marketing is not speeding up and increasing the rate and lowering the cost of doing bad marketing. >> No, no, I mean that's exactly. >> It was marketers point. >> That's right. (laughing) You can spend a lot of money to do bad marketing. >> Let's double down on our bad marketing. Ron, thanks so much for coming on the CUBE again. Thanks for sharing the insights. It's always a pleasure to get down and dirty and peel back the onion on some of these things. Final question for you. What do you expect for the evolution for this next year. >> I think AI's going to be with us for awhile just because it's the new buzz word. We've got a couple cycles on that. >> John: It reminds me of Web 2.0, what is it? >> And that lasted for a few years as well. I think over the next year or so, we're going to see the benefits of that augmentation. We're going to, actually, see some of these micro services as people start fueling some of the tools that we already have. You're also going to see some of that further collision of ad tech and mertech. Cause everything's digital and the impact of what that means for us as marketers. >> I can't wait of the hashtag, marketing native. Cause Cloud Native is coming. Someone's going to make it up, I hope not. >> Peter: You did. >> Ron: You just did. >> Okay, Marketing Native. What does that mean? We'll do a whole segment on that. We'll get Ron to come in. Hey, thanks for coming on the CUBE. >> Thanks for having me. >> Great to see you. I'm John Furrier. Peter Burris here inside the CUBE getting all the action. Straight from the data and sharing it with you. Thank you Ron, for coming on again twice in a row, two years in a row. This is the CUBE. We'll be back with more after this short break. (lively music) >> Narrator: Robert Herjavec. >> People, obviously, know you from Shark Tank. But the Herjavec group has been, really, laser folks in cyber security. >> Cause I, actually, helped bring a product called Check Point to Canada, firewalls, URI filtering, that kind of stuff. >> But you're also an entrepreneur? And you know the business. You've been in software, in the tech business. (mumbles) you get a lot of pitches as entertainment meets business. >> On our show, we're a bubble. We don't get to do a lot of tech.

>> Announcer: Live from Munich, Germany, it's The CUBE, covering DataWorks Summit Europe 2017. Brought to you by Heartenworks. >> Okay, welcome back everyone, we are here live in Munich, Germany For DataWorks 2017, the DataWorks Summit, formally Hadoop Summit. I'm John Furrier with Silicone Angle's theCUBE, my co-host Dave Vellante, wrapping up day two of coverage here with Christoph Schubert, who's the Senior Director of SAP Big Data, handles all the go-to-market for SAP Big Data, @sapbigdata is the Twitter handle. You have a great shirt there, Go Live >> Go Live or go home. (Laughs) >> John: You guys are a part. Welcome to theCUBE. >> Christoph: Thank you, I appreciate it. >> Thanks for joining us and on the wrap up. You and I have known each other, we've known each other for a long time. We've been in many Sapphires together, we've had many conversations around the role of data, the role of architecture, the role of how organizations are transforming at the speed of business, which is SAP, it's a lot of software that powers business, under transformation right now. You guys are no stranger to analytics, we have the HANA Cloud Platform now. >> Christoph: We know a thing or two about that, yeah. (laughs) >> You know a little bit about data and legacy as well. You guys power pretty much most of the Fortune 100, if not all of them. What's your thoughts on this? >> Yeah, good point. On the topic of some numbers, about 75% of the world GDP runs through SAP systems eventually. So yes, we know a thing or two about transactional and analytical systems, definitely. >> John: And you're a partner with Hortonworks >> With Hortonworks and other Cloud providers, Hadoop Providers, certainly, absolutely but in this case, Hortonworks. We have, specifically, a solution that runs on Hadoop Spark and that allows, actually, our customers to unify much, much larger data sets with a system of records that we now do so many of them around the world for new and exciting new cases. >> And you were born in Munich. This is your hometown. >> This is actually a home gig for me, exactly. So, yes, unfortunately I'll also be presenting in English but yeah, I want to talk German, Bavarian, all the time. (laughs) >> I see my parents tonight. >> I wish we could help you >> but we don't speak Bavarian. But we do like to drink the beer though. It's the fifth season but a lot of great stuff here in Germany. Dave, you guys, I want to get your thoughts on something. I wanted to get you, just 'cause you're both, you're like an analyst, Christoph as well. I know you're over at SAP but, you know, you have such great industry expertise and Dave obviously covers the stuff everyday. I just think that the data world is so undervalued, in my mind. I think the ecosystem of startups that are coming out in the, out of the open source ecosystems, which are well-defined, by the way, and getting better. But now you have startups doing things like VIMTEC, we just had a bank on. Startups creating value and things like block chain on the horizon. Other new paradigms are coming on, is going to change the landscape of how wealth is created and value is created and charged. So, you've got a whole new tsunami of change. What's your thoughts on how this expands and obviously, certainly, Hortonworks as a public company and Cloudera is going public, so you expect to see that level up in valuation. >> They're in the process, yes. >> But I still think they're both undervalued. Your thoughts. >> Well it's not just the platform, right? and that what, I think, where Hadoop also came from. The legacy of Hadoop is that you don't have to really think about how you want to use your data. You have to, don't think ahead what kind of schema you want to apply and how you want to correlate your data. You can create a large data lake, right? That's the term that was created a long time ago, that allows customers to just collect all that data and think in the second stage about what to use with it and how to correlate it. And that's exactly, now, we're also seeing in the third stage, to not just create analytics but also creating applications instead of analytics or on top of analytics, correlating with data that also drives the business, the core business, from an OLTP perspective or also from an OLAP perspective. >> I mean, Dave, you were the one who said Amazon's a trillion dollar TAM, will be the first trillion dollar company and you were kind of, but you looked at the thousand points of Live with Cloud enables, all these aggregated all together, what's your thoughts on valuation of this industry? Because if Hortonworks continues on this peer play and they've got Cloudera coming in and they're doing well, you could argue that they're both undervalued companies if you count the ecosystem. >> Well, we always knew that big data was going to be a heavy lift, right? And I would agree with what Christoph was saying, was that Hadoop is profound in that it was no schema on right and ship five magabytes of code to a pedabyte of data. But it was hard to get that right. And I remember something you said, John, at one of our early SAP Sapphires, When the big data meme was just coming through. You said, "You know, SAP is not just big data, it's fast data". And you were talking about bringing transaction and analytic data together. >> John: Right. >> Again, something that has only recently been enabled. And you think about, you know, continuous streaming. I think that, now, big data has sort of entered the young-adulthood phase, we're going to start seeing steep part of that S-curve returns, and I think the hype will be realized. I think it is undervalued, much like the internet was. It was overvalued, then nobody wanted to touch it, and then it became. Actually, if you think back to 1999, the internet was undervalued in terms of what it actually achieved. >> John: Yeah. >> I think the same or similar thing is going to happen with big data. And since we have an SAP guest on, I'll say as well, We all remember the early days of ERP. >> Mhm, oh yeah. >> It wasn't clear >> Nope. >> Who was going to emerge as the king. >> Right. >> There were a few solutions. You're right. >> That's right. And, as well, something else we said about big data, it was the practitioners of ERP that made the most money, that created the most value and the same thing is happening here. >> Yeah. In fact, on that topic, I believe that 2017 and 2018 will be the big years for big data, so to speak. >> John: Uh huh. >> In fact, because of some statistics. >> John: In what way? >> Well, we just did >> Adoption, S-curve? >> Right, exactly. Utilizing the value of big data. You're talking about valuation here, right? 75% of CEOs of the top 1000 believe that the next three years are more important to their business than the last 50. And so that tells me that they're willing to invest. Not just the financial market, where I believe really run the most sophisticated big data analytics and models today. They had real use cases with real results very quickly. And so, they showed many how it's done. They created sort of the new role of a data scientist. They have roles like an AML officer. It's a real job, they do nothing else but anti-money laundering, right? So, in that industry they've shown us how to do that and I think others will follow. >> Yeah, and I think that when you look at this whole thing about digital transformation, it's all about data. >> John: Yeah. >> I mean, if you're serious about digital transformation, you must become a data-driven company and you have to hop on that curb. Even if you're talking to the, you know, bank today who got on in 2014, which was relatively late, but the pace at which they're advancing is astronomical. >> John: Yeah. >> I don't remember his name, a British mathematician, created, about 11 years already, that according to the phrase "Data is the new oil". >> John: Mhm. >> And I think it's very true because crude oil, in its original form, you also can't use it. >> John: It has to be refined. >> Right, exactly. It has to be refined to actually use it and use the value of it. Same thing with data. You have to distill it, you have to correlate it, you have to align it, you have to relate it to business transactions so the business really can take advantage of it. >> And then we're seeing, you know, to your point, you've got, I don't know, a list of big data companies that are now in public is growing. It's still small, not much profit. >> I mean, I just think, and this is while I'm getting your reaction, I mean, I'm just reading right now some news popping on my dashboard. Google just released some benchmarks on the TPU, the transistor processing unit, >> Dave: Right. >> Basically a chip dedicated to machine learning. >> Yep. >> You know, so, you're going to start to see some abstraction layers develop, whether it's a hardened-top processor hardware, you guys have certainly done innovation on the analytic side, we've seen that with some of the specialty apps. Just to make things go faster. I mean, so, more and more action is coming, so I would agree that this S-curve is coming. But the game might shift. I mean, this is not an easy, clear path. There's bets being made in big data and there's potential for huge money shift, of value. >> See, one of the things I see, and we talked to Hortonworks about this, the new president, you know, betting all on open source. I happen to think a hybrid model is going to win. I think the rich get richer here. SAP, IBM, even Oracle, you know, they can play the open source game and say, "Hey, we're going to contribute to open source, we're going to participate, we're going to utilize open source, but we're also going to put the imprimatur of our install base, our business model, our trusted brands behind so-called big data." We don't really use that term as much anymore. It's the confluence of not only the technology but the companies who, what'd you say, 75% of the world's transactions run though SAP at some point? >> Christoph: Yeah. >> With companies like SAP behind it, and others, that's when this thing, I think, really takes off. >> What I think a lot of people don't realize, and I've been a customer, also, for a long time before I joined the vendor side, and what is under-realized is the aspect of risk management. Once you have a system and once you have business processes digitized and they run your business, you can't introduce radical changes overnight as quickly anymore as you'd like or your business would like. So, risk management is really very important to companies. That's why you see innovation within organizations not necessarily come from the core digitization organization within their enterprise, it often happens on the outside, within different business units that are closer to the product or to the customer or something. >> Something else that's happening, too, that I wanted to address is this notion of digitization, which is all about data, allows companies to jump industries. You're seeing it everywhere, you're seeing Amazon getting into content, Apple getting into financial services. You know, there's this premise out there that Uber isn't about taxicabs, it's about logistics. >> John: Yeah. >> And so you're seeing these born-digital, born in the cloud companies now being able to have massive impacts across different industries. Huge disruption creates, you know, great opportunities, in my view. >> Christoph: Yeah. >> David: What do you think? >> I mean, I just think that the disruption is going to be brutal, and I want to, I'm trying to synthesize what's happening in this show, and you know, you're going to squint through all the announcements and the products, really an upgrade to 2.6, a new data platform. But here in Europe the IOT thing just, to me, is a catalyst point because it's really a proof point to where the value is today. >> David: Mhm. >> That people can actually look at and say, "This is going to have an impact on our business tier digitization point" and I think IOT is pulling the big data industry and cloud together. And I think machine learning and things that come over the top on it are only going to make it go faster. And so that intersection point, where the AI, augmented intelligence, is going to come in, I think that's where you're going to start to see real proof points on value proposition of data. I mean, right now it's all kind of an inner circle game. "Oh yeah, got to get the insights, optimize this process here and there" and so there's some low hanging fruit, but the big shifting, mind blowing, CEO changing strategies will come from some bigger moves. >> To that point, actually, two things I want to mention that SAP does in that space, specifically, right? Startups, we have a program actually, SAP.io, that Bill McDermont also recently introduced again, where we invest in startups in this space to help foster innovation faster, right? And also connecting that with our customers. >> John: What is it called? >> SAP.io Something to look out for. And on the topic of IOT, we made, also, an announcement at the beginning of the year, Project Leonardo. >> Yeah. >> It's a commitment, it's a solution set, and it's also an investment strategy, right? We're committed in this market to invest, to create solutions, we have solutions already in the cloud and also in primus. There are a few companies we also purchased in conjunction with Loeonardo, RT specifically. Some of our customers in the manufacturing space, very strong opportunity for IOT, sensor collection, creating SLAs for robotics on the manufacturing floor. For example, we have a complete solution set to make that possible and realize that for our customers and that's exactly a perfect example where these sensor applications in IOT, edge, compute rich environments come together also with a core where, then, a system of references like machine points, for example, matter because if you manage the SLA for a machine, for example, you just not only monitor it, you want to also automatically trigger the replacement of a part, for example, and that's why you need an SAP component, as well. So, in that space, we're heavily investing, as well. >> The other think I want to say about IOT is, I see it, I mean, cloud and big data have totally disrupted the IT business. You've seen Dell buying EMC, HP had to get out of the cloud business, Oracle pivoted to the cloud, SAP obviously, going hard after the cloud. Very, very disruptive, those two trends. I see IOT as not necessarily disruptive. I see those who have the install base as adopting IOT and doing very, very well. I think it's maybe disruptive to the economy at large, but I think existing companies like GE, like Siemens, like Dimar, are going to do very, very well as a result of IOT. I mean, to the extent they embrace digitization, which they would be crazy not to. >> Alright guys, final thoughts. What's your walkaway from this show? Dave, we'll start with you. >> I was going to say, you know, Hadoop has definitely not failed, in my mind, I think it's been wildly successful. It is entering this new phase that I call sort of young-adulthood and I think it's, we know it's gone mainstream into the enterprise, now it's about, okay, how do I really drive the value of data, as we've been discussing, and hit that steep part of the S-curve. Which, I agree, it's going to be within the next two years, you're going to start to see massive returns. And I think this industry is going to be realized, looked back, it was undervalued in 2017. >> Remember how long it took to align on TCP/IP? (laughter) >> Walk away, I mean interoperability was key with TCP/IP. >> Christoph: Yeah. One of the things that made things happen. >> I remember talking about it. (laughter) >> Yeah, two megabits per second. Yeah, but I mean, bringing back that, what's your walkaway? Because is it a unification opportunity? Is it more of an ecosystem? >> A good friend of mine, also at SAP on the West Coast, Andreas Walter, he shared an observation that he saw in another presentation years ago. It was suits versus hoodies. Different kind of way to run your IT shop, right? Top-down structure, waterfall projects, and suits, open source, hack it, quickly done, you know, get in, walk away, make money. >> Whoa, whoa, whoa, the suits were the waterfall, hoodies was the agile. >> Christoph: That's correct. >> Alright, alright, okay. >> Christoph: Correct. So, I think that it's not just the technology that's coming together, it's mindsets that are coming together. And I think organizationally for companies, that's the bigger challenge, actually. Because one is very subscribed, change control oriented, risk management aware. The other is very progressive, innovative, fast adopters. That these two can't bring those together, I think that's the real challenge in organizations. >> John: Mhm, yeah. >> Not the technology. And on that topic, we have a lot of very intelligent questions, very good conversations, deep conversations here with the audience at this event here in Munich. >> Dave, my walkaway was interesting because I had some preconceived notions coming in. Obviously, we were prepared to talk about, and because we saw the S1 File by Cloudera, you're starting to see the level of transparency relative to the business model. One's worth one billion dollars in private value, and then Hortonworks pushing only 2700 million in a public market, which I would agree with you is undervalued, vis a vis what's going on. So obviously, you're going to see my observation coming in from here is that I think that's going to be a haircut for Cloudera. The question is how much value will be chopped down off Cloudera, versus how much value of Hortonworks will go up. So the question is, does Cloudera plummit, or does Cloudera get a little bit of a haircut or stay and Hortonworks rises? Either way, the equilibrium in the industry will be established. The other option would be >> Dave: I think the former and the numbers are ugly, let's not sugarcoat it. And so that's got to change in order for this prediction that we're making. >> John: Former being the haircut? >> Yeah, the haircut's going to happen, I think. But the numbers are really ugly. >> But I think the question is how far does it drop and how much of that is venture. >> Sure. >> Venture, arbitrage, or just how they are capitalized but Hortonworks could roll up. >> But my point is that those numbers have to change and get better in order for our prediction to come true. Okay, so, but in your second talk, sorry to interrupt you but >> No, I like a debate and I want to know where that line is. We'll be watching. >> Dave: Yeah. >> But the value in, I think you guys are pointing out but I walk away, is IOT is bigger here, and I already said that, but I think the S-curve is, you're right on. I think you're going to start to see real, fast product development around incorporating data, whether that's a Hortonworks model, which seems to be the nice unifying, partner-oriented one, that's going to start seeing specialized hardware that people are going to start building chips for using flash or other things, and optimizing hard complexities. You pointed that out on the intro yesterday. And putting real product value on the table. I think the cards are going to start hitting the table in ecosystem, and what I'm seeing is that happening now. So, I think just an overall healthy ecosystem. >> Without a doubt. >> Okay. >> Great. >> Any final comments? >> Let's have a beer. >> Great to see you in Munich. (laughter) >> We'll have a beer, we had a pig knuckle last night, Dave. We had some sauerkraut. >> Christoph: (speaks foreign word) >> Yeah, we had the (speaks foreign word). Dave, we'll grab the beer, thanks. Good to be with you again. Thanks to the crew, thanks to everyone watching. >> Thanks, John. >> The CUBE, signing off from Munich, Germany for DataWorks 2017. Thanks for watching, see ya next time. (soft techno music)